Developing Generative AI Applications on AWS

Agenda

Module 1: Exploring Components of Generative AI Applications on AWS

• Understanding generative AI concepts
• Identifying AWS generative AI stack components
• Designing generative AI application components

Module 2: Programming with Amazon Bedrock

• Guiding model response generation
• Using Amazon Bedrock programmatically

Module 3: Applying Prompt Engineering for Developers

• Introducing prompt engineering
• Introducing prompt techniques
• Optimizing prompts for better results

Module 4: Using Amazon Bedrock APIs in Common Architectures

• Implementing architecture patterns with Amazon Bedrock APIs
• Exploring common use cases
• Adding conversational memory to extend context

Module 5: Customizing Generative AI Responses with RAG

• Implementing Retrieval Augmented Generation (RAG)
• Using Amazon Bedrock Knowledge Bases

Module 6: Integrating Open Source Frameworks with Amazon Bedrock

• Invoking a foundation model in Amazon Bedrock using LangChain
• Using LangChain for context-aware responses

Module 7: Evaluating Generative AI Application Components

• Evaluating application components
• Evaluating model output
• Evaluating RAG output
• Optimizing latency and cost

Module 8: Implementing Responsible AI

• Understanding responsible AI
• Mitigating bias and addressing prompt misuses
• Using Amazon Bedrock Guardrails

Module 9: Using Tools and Agents in Generative AI Applications

• Using tools
• Understanding AI agents
• Understanding open source agentic frameworks
• Understanding agent interoperability

Module 10: Developing Amazon Bedrock Agents

• Implementing Amazon Bedrock Flows
• Designing Amazon Bedrock Agents
• Developing Amazon Bedrock Inline Agents
• Designing multi-agent collaboration
• Using Amazon Bedrock AgentCore